The tropical cyclonic strong wind and storm surge model use information from 2594 historical tropical cyclones, topography, terrain roughness, and bathymetry. The historical tropical cyclones used in GAR15 cyclone wind and storm surge model are from five different oceanic basins: Northeast Pacific, Northwest Pacific, South Pacific, North Indian, South Indian and North Atlantic and the tracks were obtained from the IBTrACS database (Knapp et al. 2010). This database represents the repository of information associated with tropical cyclones that is the most up to date. Topography was taken from the Shuttle Radar Topography Mission (SRTM) of NASA, which provides terrain elevation grids at a 90 meters resolution, delivered by quadrants over the world. To account for surface roughness, polygons of urban areas worldwide were obtained from the Socioeconomic Data and Applications Centre, SEDAC (CIESIN et al., 2011). This was considered a good proxy of the spatial variation of surface roughness. A digital bathymetry model is employed with a spatial resolution of 30 arc-seconds, taken from the GEBCO_08 (General Bathymetric Chart of the Oceans) Grid Database of the British Oceanographic Data Centre (2009). Bathymetry is the information about the underwater floor of the ocean having direct influence on the formation of the storm surge. More information about the cyclone wind and strom surge hazard can be found in CIMNE et al., 2015a. Hazard analysis was performed using the software CAPRA Team Tropical Cyclones Hazard Modeler (Bernal, 2014). The vulnerability models used in the risk calculation for GAR correlate loss to the wind speed for 3-seconds gusts. For GAR15, the risk was calculated with the CAPRA-GIS platform which is risk modelling tool of the CAPRA suite (www.ecapra.org). The risk assessment was also conducted by CIMNE and Ingeniar to produced AAL and PML values for cyclone risk.

Extreme high temperatures: areas where the number of days per year with maximum temperatures above 35ºC will increase by more than 15 days. The long-term change in annual max temperature is calculated over a 20 year time period, from 2041 to 2060 (mid term) and with RCP 2.6 low emissions scenario. Source: WCRP CORDEX - CMIP6/CORDEX (https://cordex.org/experiment-guidelines/cordex-cmip6/)

Ocean temperature: areas where the temperature of the sea at surface level is above 25ºC. The long-term change in annual ocean temperature is calculated over a 20 year time period, from 2041 to 2060 (mid term) and with RCP 2.6 low emissions scenario. Source: ????

This dataset assesses the current and future weather-related hazards that are likely to affect the agricultural systems (including crops, fisheries/aquaculture, livestock, and forestry) and the population in the project’s locations. Reference time period: Medium term (2041-2060); Reference climate scenario=RCP2.6 (Low emissions)

Drought: areas where the change in the Standardized Precipitation Index (SPI) is below -20%. The long-term change in annual drought is calculated over a 20 year time period, from 2041 to 2060 (mid term), with RCP 2.6 low emission scenario. Source: WCRP CORDEX - CMIP6/CORDEX (https://cordex.org/experiment-guidelines/cordex-cmip6/)

The HDI was created to emphasize that people and their capabilities should be the ultimate criteria for assessing the development of a country, not economic growth alone. The HDI can also be used to question national policy choices, asking how two countries with the same level of GNI per capita can end up with different human development outcomes. These contrasts can stimulate debate about government policy priorities. The Human Development Index (HDI) is a summary measure of average achievement in key dimensions of human development: a long and healthy life, being knowledgeable and have a decent standard of living. The HDI is the geometric mean of normalized indices for each of the three dimensions. The health dimension is assessed by life expectancy at birth, the education dimension is measured by mean of years of schooling for adults aged 25 years and more and expected years of schooling for children of school entering age. The standard of living dimension is measured by gross national income per capita. The HDI uses the logarithm of income, to reflect the diminishing importance of income with increasing GNI. The scores for the three HDI dimension indices are then aggregated into a composite index using geometric mean. Refer to Technical notes for more details. The HDI simplifies and captures only part of what human development entails. It does not reflect on inequalities, poverty, human security, empowerment, etc. The HDRO offers the other composite indices as broader proxy on some of the key issues of human development, inequality, gender disparity and poverty. A fuller picture of a country's level of human development requires analysis of other indicators and information presented in the statistical annex of the report.

Extreme low temperatures: Areas where minimum temperatures are below 0ºC for at least 15 days on average per year. The long-term change in annual minimum temperature is calculated over a 30 year time period, from 1981 to 2010 (baseline). Source: CHIRPS/GEE 2015.

This dataset assesses the risks for a system or a community to the adverse effects of climate change, considering the available information on the following indicators:

Extreme low temperatures: areas where the number of days per year with minimum temperatures below 0ºC will increase by more than 1 day. The long-term change in annual min temperature is calculated over a 20 year time period, from 2021 to 2040 (near term) and with RCP 2.6 low emission scenario. Source: WCRP CORDEX - CMIP6/CORDEX (https://cordex.org/experiment-guidelines/cordex-cmip6/).

Extreme high temperatures: areas where the number of days per year with maximum temperatures above 35ºC will increase by more than 15 days. The long-term change in annual max temperature is calculated over a 20 year time period, from 2021 to 2040 (near term) and with RCP 2.6 low emissions scenario. Source: WCRP CORDEX - CMIP6/CORDEX (https://cordex.org/experiment-guidelines/cordex-cmip6/)